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Emerging Methods for Patient Ergonomics
Published in Richard J. Holden, Rupa S. Valdez, The Patient Factor, 2021
Mustafa Ozkaynak, Laurie Lovett Novak, Yong K. Choi, Rohit Ashok Khot
Sleep self-management strategies that incorporate sensors have the potential to empower patients to track and improve their sleep quality. With the uptake of smartphone ownership, Depose have been developed that utilize embedded sensors in a smartphone to self-monitor activity levels and visualize sleep patterns. Such apps often instruct a user to connect the phone to the charger and place it on the sleeping surface or under the pillow to passively collect data. Using the data, the sleep tracking apps can provide information on sleep patterns (e.g., bedtime, wakeup time, and average time in bed). Additionally, consumer-grade wearable devices such as wrist-worn activity trackers and smart watches also provide users with estimates of sleep-related parameters using proprietary algorithms, including the amount of time in light, deep, and rapid eye movement stage of sleep (Choi et al., 2018). The wearables can collect biometric parameters such as heart rate and blood pressure and potentially provide more detailed estimates than smartphone sensor-based apps. However, sleep estimates generated by wearable devices are under scrutiny for inaccuracy and cannot be used as a substitute for data collected by polysomnography in a sleep lab (Haghayegh et al., 2019). The limitations of wrist-worn sensors also include limited battery life and discomfort of wearing the device during sleep. Despite the shortcomings, consumer-grade IoT sensors provide simple and economical means to longer-term sleep monitoring.
Green Healthcare for Smart Cities
Published in Pradeep Tomar, Gurjit Kaur, Green and Smart Technologies for Smart Cities, 2019
Prabhjot Singh, Varun Dixit, Jaspreet Kaur
No one can deny the fact that proper sleep is a must for maintaining good health. On this concept, there are a number of devices that can track and monitor sleep patterns of consumers. For example, Apple Watch, Fitbit Ionic, Emfit QS, Jawbone UP3 and Motiv Ring are some of the devices that are trending in the market for sleep tracking. MYIA Labs place sensors under the bed to track heart rate and breathing levels of a sleeping person (How Wearables Will 2019). Further, active feedback sensors are being innovated which can play calm music whenever a sensor detects a patient stirring. The kinetic energy of the patient can power these devices and underlying sensors.
Do objective data support the claim that problematic smartphone use has a clinically meaningful impact upon adolescent sleep duration?
Published in Behaviour & Information Technology, 2022
Saoirse Mac Cárthaigh, John Perry, Claire Griffin
Commercial sleep tracking devices use the same technology as research-grade actigraphy (i.e. writs-mounted accelerometers). In addition, some models detect sleep or wake states by assessing changes in heart rate using technology known as optical plethysmography (Grandner and Rosenberger 2019). Over the past few years, validation research has begun to support the use of these affordable commercial sleep tracking devices (e.g. de Zambotti et al. 2016; de Zambotti et al. 2018; Degroote et al. 2020; Dickinson, Cazier, and Cech 2016; El-Amrawy and Nounou 2015; Henriksen et al. 2020; Kang et al. 2017; Lee et al. 2017; Lerner et al. 2018; Liang and Martell 2018; Montgomery-Downs, Insana, and Bond 2012; Pesonen and Kuula 2018; Stone et al. 2020; Tedesco et al. 2019). While commercial sleep trackers do not yet validly or reliably measure sleep staging (e.g. Lee et al. 2019; Liang and Martell 2018), they have comparable validity to gold-standard sleep measurement approaches on sleep parameters such as total sleep time and time in bed (e.g. de Zambotti et al. 2016; Kang et al. 2017). The use of these affordable devices could help to address the sample size limitations of previous research on the relationship between sleep and PSU.